Wireless Hybrid Enhanced Mobile Radio Estimators

WHERE

Presented bySuji Gunaratne PhD

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Motivation - Why do we need WHERE ? Partners and their Role in WHERE Objectives of WHERE and WPs WHERE IT Contributions

WHERE - Outline

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Challenges for future networks covered by project objectives

Localisation information is used to:

PHY Layer enhancements Cross-layer optimisation for

PHY/MAC Enhanced Relaying and

Cooperative Communication RAT selection policies and

optimisation

Communication information is used to:

Estimation of location-dependent channel parameters

Fingerprint-based localization Hybrid Data Fusion and Tracking Cooperative Positioning

Why do we need WHERE ?

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The integration of communications and navigation.

Improvement of future wireless communications systems and integration of heterogeneous RAN infrastructures by location based procedures and protocols.

Estimation of MT position information based on terrestrial RANs to enable such location based RAN functions.

Exploitation of communication links to improve RAN based positioning through MT cooperation.

Provision of accurate MT position information to enable location based and context aware services.

Main Objectives

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Surrounding mobiles know and provide their position information (e.g. by broadcasting or by answering a ‘ping’)

A less equipped mobile can receive this information via short range communication such as ZigBee or UWB

The mobile position is the intersection of several circles

Works well in dense populated areas.

Maybe such areas coincide with those, where pure GNSS positioning is difficult to achieve

Mobile with GNSS

Short range communication

Goodknowledgeof position

Less equipped mobile

Hybrid/Cooperative Positioning

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Topic: Cooperative mobile radio communications and localisation

EU Project Proposal: Type: STREP Duration: 30 Months Volume: 529 PMs, 5.5 M€ (73% funding = 4.04 M€)

Goals: Optimise ubiquitous and converged network and service

infrastructures for communication and media• Adaptive and predictive communications exploiting

location positioning information for future systems with multiple capabilities on PHY/MAC layer

• Improvement of localisation for indoor and urban canyons

Project Overview

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Industrial partners Mitsubishi Electric ITE (F)

SMEs ACORDE (E) SigINT (CY) Siradel (F)

Universities AAU (DK) UniS (GB) IETR (F) IT (P) UPM (E)

R&D Centres CEA-LETI (F) DLR (D) Eurecom (F)

Outside Europe University of Alberta (CDN) City University of Hong Kong

(CN)

Partnership: 12 (+2) partners, 7 (9) countries

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Early Milestone: Scenarios to be investigated in the algorithmic WPs and the

demonstration WP – needs to be restricted: Indoor vs. outdoor (urban canyon), Synchronised vs.

non-synchronised, Static vs. Dynamic positioning, SISO vs. MISO vs. MIMO, Single vs. multi-cell, Single vs. cooperative system

Scenarios to synchronise different hardware platforms Appropriate parameters derived from other IST projects and

standardisation processes

Late Milestone: Parameters may be redefined (e.g. communication systems

that do not take positioning into account so far)

WP1: Scenarios and Framework Definition

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Hybrid Data Fusion and Tracking Cooperative Positioning

PHY Layer enhancements using localisation data Location based cross-layer optimisation for PHY/MAC Enhanced relaying and cooperative communication using

positioning data RAT selection policies and optimisation

WP2: Hybrid and Cooperative Positioning

WP3: Navigation-aided Cellular Communications

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Channel measurements • Creating a fingerprinting data base

Mobility model based on the channel measurements Investigation of location-dependent channel parameters Fingerprint-based localization

Exploiting former platforms – get some enhancements to work with higher accuracy for localisation

• 3GPP LTE devices• UWB devices• Zigbee devices• Wi-Fi devices

WP4: Channel Characteristion

WP5: Demonstration

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WHERE IT Contributions I Location assisted RAT selection for B3G Network optimisation

In this scenario it is assumed that the test mobile terminal is a multimode one and that the location of the mobile in both networks are available.

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WHERE IT Contributions II

The fact that the mobile can reach more than one network can be exploited towards providing more than one alternatives to questions like:

Detection: What RATs are currently available? Selection: What RAT to choose; which is “best”?, one or

multiple RATs in parallel? Criteria for RAT selection includes QoS, resource usage in terms of codes, power, channel conditions, etc...)

Reselection: Under what conditions reselection is necessary; which network to choose? How reselection is accomplished. Can we anticipate a reselection procedure?

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WHERE IT Contributions III

Task 2.2 Cooperative PositioningCooperative Positioning

To investigate algorithms/protocols for distributed processing to allow:

Node discovery; how do we identify suitable cooperative nodes.Node selection. How to identify the “best nodes” to participate in

cooperative dialogue; technique required for selecting the most useful nodes that would provide the most accurate positional estimationhow to fuse the data between the selected cooperating nodes to enhance the positional estimation.

Node reselection. How to we use positional information to reselect new nodes in case of link failure.

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WHERE IT Contributions IV

Task 3.2: Location based cross-layer optimization for PHY/MACTo investigate cross-layer optimization strategies for radio resource management protocols and algorithms that exploit positioning data, based on the underlying PHY layer enhancements from Task 3.1

Management ResponsibilitiesWP3 Leader : Navigation-aided cellular communication systemsTask 3.2 Leader: Location based cross-layer optimization for PHY/MAC

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Wireless Hybrid Enhanced Mobile Radio Estimators

Project Coordinator:Ronald RaulefsInstitute of Communications and NavigationGerman Aerospace Center (DLR)Oberpfaffenhofen, GermanyEmail: {Armin.Dammann, Ronald.Raulefs}@DLR.de

IT Coordinator:Jonathan RodriguezEmail: jonathan@av.it.pt

Thank you